Borderline SMOTE Algorithm and Feature Selection‐Based Network Anomalies Detection Strategy

Borderline SMOTE Algorithm and Feature Selection‐Based Network Anomalies Detection Strategy

This paper proposes a novel network anomaly detection framework based on data balance and feature selection. Different from the previous binary classification of network intrusion, the network anomaly detection strategy proposed in this paper solves the problem of multiple classification of network...

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Bibliographic Details
Main Authors: Cai, Q. (Author), Kong, Z. (Author), Li, J. (Author), Que, H. (Author), Sun, Y. (Author), Wang, S. (Author), Zhao, J. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Algorithm selection
Anomaly detection
borderline SMOTE
Borderline SMOTE
Decision trees
Feature Selection
Features selection
information gain ratio
Information gain ratio
Intrusion detection
Learning algorithms
machine learning
Machine-learning
Network anomaly detection
network intrusion detection
Network intrusion detection
Network intrusions
Selection based
SMOTE algorithm
Online Access:View Fulltext in Publisher

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